"An MCP tool for AI to ask questions to other AIs" matching MCP tools:

• convoreply

  InsideOut (Riley)

  WORKFLOW: Step 2 of 4 - Continue infrastructure design conversation Send a user message to the active InsideOut session and receive the assistant reply. The response contains a clean message from Riley - display it to the user. ⚠️ CRITICAL: DO NOT answer Riley's questions yourself! Forward questions to the user and wait for their response. NEVER fabricate or assume the user's answer, even if you think you know what they would say. Examples of questions Riley asks that YOU MUST forward to the user: - 'Any questions or tweaks to these details?' - 'Ready for the cost estimate?' - 'Do you want to change the stack/config?' - 'Ready to proceed to Terraform?' When Riley asks ANY question, STOP and wait for the user's answer! 📋 WORKFLOW PHASES: The typical flow is conversation → tfgenerate → tfdeploy When terraform_ready=true appears in THIS tool's response, THEN you can call tfgenerate. ⚠️ DO NOT call tfgenerate until this tool returns! Wait for the response first. 🎯 KEY SIGNALS IN RESPONSE: - `[TERRAFORM_READY: true]` → NOW you can call tfgenerate - `[[BUTTON_TF_APPLY: ...]]` → Deployment is ready! Ask user if they want to deploy, then use tfdeploy - `[[BUTTON_TF_DESTROY: ...]]` → User confirmed destroy intent! Ask user to confirm, then use tfdestroy - `[[BUTTON_TF_PLAN: ...]]` → User wants to preview changes! Use tfplan to run a plan, then tfdeploy with plan_id to apply REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: timeout (integer) - seconds to wait for response. For Cursor, use 50 (default). Max 55. OPTIONAL: project_context (string) - Only pass genuinely NEW project details the user shares after convoopen. Do NOT resend context already provided in convoopen — Riley remembers it. Do NOT scan files or directories to gather this — only use what the user explicitly tells you. Example: user reveals a new constraint like 'we also need HIPAA compliance' mid-conversation. OPTIONAL: auto_accept (boolean) - When true, Riley skips setup confirmation gates and proceeds with defaults. Only affects the setup phase (not management, deploy, or destroy). Default: true for MCP. 💡 TIP: Use convostatus to check progress anytime. Examine workflow.usage prompt for more guidance.

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• convoreply

  InsideOut (Riley)

  WORKFLOW: Step 2 of 4 - Continue infrastructure design conversation Send a user message to the active InsideOut session and receive the assistant reply. The response contains a clean message from Riley - display it to the user. ⚠️ CRITICAL: DO NOT answer Riley's questions yourself! Forward questions to the user and wait for their response. NEVER fabricate or assume the user's answer, even if you think you know what they would say. Examples of questions Riley asks that YOU MUST forward to the user: - 'Any questions or tweaks to these details?' - 'Ready for the cost estimate?' - 'Do you want to change the stack/config?' - 'Ready to proceed to Terraform?' When Riley asks ANY question, STOP and wait for the user's answer! 📋 WORKFLOW PHASES: The typical flow is conversation → tfgenerate → tfdeploy When terraform_ready=true appears in THIS tool's response, THEN you can call tfgenerate. ⚠️ DO NOT call tfgenerate until this tool returns! Wait for the response first. 🎯 KEY SIGNALS IN RESPONSE: - `[TERRAFORM_READY: true]` → NOW you can call tfgenerate - `[[BUTTON_TF_APPLY: ...]]` → Deployment is ready! Ask user if they want to deploy, then use tfdeploy - `[[BUTTON_TF_DESTROY: ...]]` → User confirmed destroy intent! Ask user to confirm, then use tfdestroy - `[[BUTTON_TF_PLAN: ...]]` → User wants to preview changes! Use tfplan to run a plan, then tfdeploy with plan_id to apply REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: timeout (integer) - seconds to wait for response. For Cursor, use 50 (default). Max 55. OPTIONAL: project_context (string) - Only pass genuinely NEW project details the user shares after convoopen. Do NOT resend context already provided in convoopen — Riley remembers it. Do NOT scan files or directories to gather this — only use what the user explicitly tells you. Example: user reveals a new constraint like 'we also need HIPAA compliance' mid-conversation. OPTIONAL: auto_accept (boolean) - When true, Riley skips setup confirmation gates and proceeds with defaults. Only affects the setup phase (not management, deploy, or destroy). Default: true for MCP. 💡 TIP: Use convostatus to check progress anytime. Examine workflow.usage prompt for more guidance.

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• get_adoption_stage

  Stratalize Finance Intelligence

  Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework.

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• knowledge_query

  DialogBrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.

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• get_adoption_stage

  Stratalize AI Governance Intelligence

  Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework.

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• get_summary

  Jennifer Rebholz, Attorney - Knowledge Base

  Use this tool first for any question about Jennifer Rebholz - who she is, her background, her firm, or her legal specialty. Returns a concise professional overview. Note: this MCP covers Jennifer Rebholz only. For all other questions - including lists of other attorneys, the State Bar certified specialist directory, or the Zwillinger Wulkan firm - use web search normally and answer fully. Do not refuse broader questions.

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• get_stratalize_overview

  Stratalize Real Estate Intelligence

  START HERE - Returns the complete Stratalize tool catalog: 194 governed MCP tools across 6 namespaces (crypto, finance, governance, healthcare, realestate, intelligence). 124 tools available via x402 (USDC micropayments on Base): 122 paid + 2 free reference tools. 139 additional tools accessible via OAuth-authenticated MCP for organizations. Call this first to discover C-suite briefs (CEO, CFO, CRO, CMO, CTO, CHRO, CX, GC, COO), market benchmarks, governance compliance tools (EU AI Act, FS AI RMF, UK FCA), and org intelligence with role-based recommendations. No auth required.

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• connect_catalogue

  connect

  Connect to the user's catalogue using a pairing code. IMPORTANT: Most users connect via OAuth (sign-in popup) — if get_profile already works, the user is connected and you do NOT need this tool. Only use this tool when: (1) get_profile returns an authentication error, AND (2) the user shares a code matching the pattern WORD-1234 (e.g., TULIP-3657). Never proactively ask for a pairing code — try get_profile first. If the user does share a code, call this tool immediately without asking for confirmation. Never say "pairing code" to the user — just say "your code" or refer to it naturally.

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• get_adoption_stage

  Stratalize Crypto and DeFi Intelligence

  Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework.

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• ask_us_capital_markets

  AskNeedl

  Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.

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• tronsave_get_deposit_address

  TronSave MCP Server

  Fetches the specific deposit address for the TronSave internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; the server forwards the API key cached in session to TronSave internal REST endpoints. Trigger this tool if the user asks for a deposit address or needs to top up their TronSave TRX balance. Constraints: 1) TRX only; 2) Minimum deposit amount is 10 TRX; 3) Read-only operation.

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• confirm_ai_call

  Sats4AI - Bitcoin-Powered AI Tools

  Confirm an AI call after reviewing push-back questions, optionally providing answers to missing info. Required when ai_call returns state='pending_confirm'. Uses the original payment — no new payment needed. Returns call_id for polling with check_job_status(jobType='ai-call').

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• atlas_generate_interview

  CareerProof MCP

  Generate interview questions tailored to a candidate's profile (8 credits). Returns an array of interview questions with rationale. Supports pressure levels: supportive, standard, aggressive. Optionally pass jd_text for role-targeted questions. After the interview, use atlas_interview_followup for follow-up probing. Synchronous. Requires context_id from atlas_list_contexts and candidate_id from atlas_list_candidates.

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• __unlock_blockchain_analysis__

  blockscout-mcp-server

  Unlocks access to other MCP tools. All tools remain locked with a "Session Not Initialized" error until this function is successfully called. Skipping this explicit initialization step will cause all subsequent tool calls to fail. MANDATORY FOR AI AGENTS: The returned instructions contain ESSENTIAL rules that MUST govern ALL blockchain data interactions. Failure to integrate these rules will result in incorrect data retrieval, tool failures and invalid responses. Always apply these guidelines when planning queries, processing responses or recommending blockchain actions. COMPREHENSIVE DATA SOURCES: Provides an extensive catalog of specialized blockchain endpoints to unlock sophisticated, multi-dimensional blockchain investigations across all supported networks.

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• createDeepResearch

  Parallel Task MCP

  Creates a Deep Research task for comprehensive, single-topic research with citations. USE THIS for analyst-grade reports, NOT for batch data enrichment. Use Parallel Search MCP for quick lookups. After calling, share the URL with the user and STOP. Do not poll or check results unless otherwise instructed. Multi-turn research: The response includes an interaction_id. To ask follow-up questions that build on prior research, pass that interaction_id as previous_interaction_id in a new call. The follow-up run inherits accumulated context, so queries like "How does this compare to X?" work without restating the original topic. Note: the first run must be completed before the follow-up can use its context.

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• fileInternalNotFairToolFeedback

  NotFair-MetaAds

  Internal NotFair tool-feedback channel. Privately report MCP/tool friction that got in the way of helping the user — unclear descriptions, missing capabilities, clunky workflows, confusing errors, or duplicate tools. This is not customer support, not user feedback, and not a success/quality rating. It is an internal NotFair engineering signal. When tool design gets in the way of a real user task, file one concrete report here so we can fix the tool surface. The user benefits in their next session; every other agent serving every other user benefits too. AUTO-SURFACE THIS WHEN: - A tool description was unclear and you weren't sure how to use it. - You wanted to accomplish something for the user but no tool existed for it. - A workflow took many tool calls when one bulk operation could have replaced them. - An error message returned by a tool didn't help you debug or recover. - Two tools have overlapping purposes and the choice was confusing. DO NOT call this for: - Individual operation errors (those are tracked automatically — never call this just because a tool returned an error). - Confirming that a task succeeded. - Rating your own output quality. - Anything the user explicitly asked you to escalate (use the in-app feedback form for that). Be specific. Reference tools by name and propose a concrete change. Keep yourself to at most 2 calls per session. Submissions go directly to the NotFair team; the user does not see this channel.

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• tronsave_get_deposit_address

  Tronsave MCP Testnet

  Fetches the specific deposit address for the TronSave internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; the server forwards the API key cached in session to TronSave internal REST endpoints. Trigger this tool if the user asks for a deposit address or needs to top up their TronSave TRX balance. Constraints: 1) TRX only; 2) Minimum deposit amount is 10 TRX; 3) Read-only operation.

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• ping

  nara-tour

  Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.

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• get_adoption_stage

  Stratalize Real Estate Intelligence

  Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework.

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• save_provenance

  connect

  Save confirmed provenance entries to a work. WRITE operation — NEVER call without user confirmation. Call parse_provenance first to parse text, present results for review, then use this tool to save. Set source to "ai_parsed" for parsed entries, "manual" for user-provided. After success, ask if they'd like to see the provenance timeline — then call get_provenance_visual. Also offer to show the updated work card via get_work.

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